1. Field of the Invention
The present invention generally relates to surveillance systems and methods for providing security, and, more particularly to a novel system and process for analyzing video taken from a non-static, i.e., moving, camera.
2. Description of the Prior Art
It is expected that for some time to come, camera devices will not be of sufficiently high resolution to acquire sufficient resolution images for some tasks, e.g., surveillance, over wide fields of view. High resolution cameras are expensive, and to cover wide areas they need special lenses that distort the images. The alternative for complete coverage is using many cameras, which is also expensive. Many current surveillance systems cover wide areas with sufficient resolution by deploying pan-tilt-zoom cameras that can be directed to an area of interest within a very large field of view, and zoomed in to give sufficient detail.
Other known systems implement manual steering, with a human operator using moving cameras executing a “tour”. Touring cameras allow coverage of a wide area with the penalty of not observing the whole area all the time. However, the operator may choose a particular area of interest and steer the camera, which is very labour intensive and prone to error, i.e., it is easy to miss important information, which may have dire consequences for critical surveillance operations. For simple recording, many surveillance sites use cameras that can be programmed to move in a predetermined sequence, called “touring”. In this way the camera scans a wide area.
Recent years have seen increasing development of automatic systems to process and “understand” video, particularly surveillance video. Such systems are designed to “watch” the video in place of a human operator, and detect interesting events, flagging them for human intervention, or logging all activity in a database which can be searched for interesting events, or compiled into statistics at a later stage. However, these systems are all designed for use with a static camera, exploiting the static nature of the image for detecting motion as an exception, using such methods as “background subtraction” or motion analysis.
Thus, typical surveillance “analytics” systems operate on video data obtained from static or fixed cameras. Processing video from a moving camera, such as a pan-tilt-zoom camera, is much more complex as methods such as background subtraction, that form the basis of most current analytics systems, need static cameras. While known solutions implement optical flow analysis techniques for explicit detection of objects in moving cameras, these are less sensitive than static camera techniques, and moreover are computationally expensive.
It would be highly desirable to provide a system and method for automatically understanding content (e.g., moving objects) in a video from a non-static camera, particularly one that benefits from the accumulated knowledge in conventional static-camera algorithms.